rasmusbergpalm

<?php
$url = 'http://cdn.armafiles.info/';
$filelist = trim(file_get_contents($url.'md5checksums.txt'));
$lines = explode("\n", $filelist);

$oldfiles = @unserialize(file_get_contents('files'));
foreach ($lines as $line) {
    list($md5, $file) = preg_split('/\s/', $line,-1,PREG_SPLIT_NO_EMPTY);
    $files[$md5] = $file;

rasmusbergpalm

#Blah bla#

rasmusbergpalm

var flattenObject = function(ob) {
    var toReturn = {};

    for (var i in ob) {
        if (!ob.hasOwnProperty(i)) continue;

        if ((typeof ob[i]) == 'object') {
            var flatObject = flattenObject(ob[i]);
            for (var x in flatObject) {
                if (!flatObject.hasOwnProperty(x)) continue;

rasmusbergpalm

^-?(\d{1,3}(\,\d{3})*|(\d+))(\.\d*)?$

rasmusbergpalm

#!/bin/bash
export STATUS="`curl -sL -w "%{http_code}" "http://169.254.169.254/latest/user-data" -o /dev/null`"
if [ "$STATUS" != "200" ]; then
  echo "exiting"
	exit 1
fi
echo "running"
export EXPERIMENT="`curl http://169.254.169.254/latest/user-data`"
s3fs <bucket> /root/s3
octave /root/research/$EXPERIMENT &> /root/s3/results/${EXPERIMENT////-}.log.txt

rasmusbergpalm

@MASTERSTHESIS\{IMM2012-06284,
    author       = "R. B. Palm",
    title        = "Prediction as a candidate for learning deep hierarchical models of data",
    year         = "2012",
    school       = "Technical University of Denmark, {DTU} Informatics, {E-}mail: reception@imm.dtu.dk",
    address      = "Asmussens Alle, Building 305, {DK-}2800 Kgs. Lyngby, Denmark",
    type         = "",
    note         = "Supervised by Associate Professor Ole Winther, owi@imm.dtu.dk, {DTU} Informatics, and Morten M{\o}rup, mm@imm.dtu.dk, {DTU} Informatics",
    url          = "http://www.imm.dtu.dk/English.aspx",
    abstract     = "Recent findings [HOT06] have made possible the learning of deep layered hierarchical representations of data mimicking the brains working. It is hoped that this paradigm will unlock some of the power of the brain and lead to advances towards true {AI}.

rasmusbergpalm

{
    "apiVersion": "1.0.0",
    "swaggerVersion": "1.2",
    "basePath": "http://petstore.swagger.wordnik.com/api",
    "resourcePath": "/user",
    "produces": [
        "application/json"
    ],
    "apis": [
        {

rasmusbergpalm

def a = [1, 2, 3, 4, 5, 6, 7, 8, 9];
def N = 3;
def buckets = [];
for (int i = 0; i < N; i++) {
    buckets[i] = [k: [], t: 0]
}
a.sort { -it }.each { i ->
    def b = buckets[0]
    b.k.push(i)
    b.t += i

rasmusbergpalm

{
  "Outcome":"NO_PERSON"
}

rasmusbergpalm

def set2vector(x, init, f, g, h, RNN, T):
  """
  x: input data w. N samples
  init: function that initializes hidden state of RNN
  f: f(x): function that maps each sample of x to a vector. E.g. the identity function, an MLP, etc.
  g: g(m,q): function that maps vectors m and q to a single number. E.g. the dot product, an MLP, etc.
  h: h(q,r): function that maps vectors q and vector r to a vector, e.g. an MLP or similar.
  T: int, how many steps to run.
  """
  qs[0] = init() # qs[t] is a vector (RNN "post" hidden state?)